Dr. Rorai Pereira Martins-Neto has a degree in Forest Engineering from the Federal University of Parana, UFPR, Brazil (2014), a Master’s degree in Forest Engineering from Santa Catarina State University, CAV-UDESC, Brazil (2016), and a PhD in Photogrammetry and Remote Sensing from the Paulista State University “Julio de Mesquita Filho” – FCT/UNESP, Brazil (2021). He is currently a postdoctoral researcher and assistant professor at the Faculty of Forestry and Wood Sciences at the Czech University of Life Sciences Prague (CULS). He has experience in photogrammetry and remote sensing applied to forestry, working mainly with forest monitoring using machine learning and computer vision techniques for the analysis and development of predictive models and classification. His research is related to the following topics: LiDAR (discrete and full waveform returns) for characterization and modeling of native and planted forests, use of multispectral and hyperspectral images for mapping tree diversity, forest health, land cover and land use, and field spectroscopy. Other relevant research topics relate to R programming, data science, and machine learning and deep learning techniques for regression and classification.